Decreased home cage movement and oromotor impairments in adult Fmr1‐KO mice

Abstract

Fragile X syndrome (FXS) is a common inherited disorder that significantly impacts family and patient day-to-day living across the entire lifespan. The childhood and adolescent behavioral consequences of FXS are well-appreciated. However, there are significantly fewer studies (except those examining psychiatric comorbidities) assessing behavioral phenotypes seen in adults with FXS. Mice engineered with a genetic lesion of Fmr1 recapitulate important molecular and neuroanatomical characteristics of FXS, and provide a means to evaluate adult behavioral phenotypes associated with FXS. We give the first description of baseline behaviors including feeding, drinking, movement, and their circadian rhythms; all observed over 16 consecutive days following extensive environmental habituation in adult Fmr1-KO mutant mice. We find no genotypic changes in mouse food ingestion, feeding patterns, metabolism, or circadian patterns of movement, feeding, and drinking. After habituation, Fmr1-KO mice demonstrate significantly less daily movement during their active phase (the dark cycle). However, Fmr1-KO mice have more bouts of activity during the light cycle compared to wildtypes. In addition, Fmr1-KO mice demonstrate significantly less daily water ingestion during the circadian dark cycle, and this reduction in water intake is accompanied by a decrease in the amount of water ingested per lick. The observed water ingestion and circadian phenotypes noted in Fmr1-KO mice recapitulate known clinical aspects previously described in FXS. The finding of decreased movement in Fmr1-KO mice is novel, and suggests a dissociation between baseline and novelty-evoked activity for Fmr1-KO mice.

Home-cage hypoactivity in mouse genetic models of autism spectrum disorder

“…Cntnap2 −/− and Fmr1 KO mice have been reported to be hyperactive in the open field (The Dutch-Belgium Fragile X Consortium, 1994; Peier et al, 2000; Mineur et al, 2002; Restivo et al, 2005; Spencer et al, 2005; Dahlhaus & El-Husseini, 2010; Yuskaitis et al, 2010; Liu et al, 2011; Peñagarikano et al, 2011; Gholizadeh et al, 2014; Uutela et al, 2014; Brunner et al, 2015) and displayed no activity differences during the habituation phase in our task (Fig. 3), but longer activity studies across multiple undisturbed days corroborate our findings of hypoactivity in Cntnap2 −/− (Thomas, Schwartz, Saxe, & Kilduff, 2016) and Fmr1 KO male mice (Bonasera, Chaudoin, Goulding, Mittek, & Dunaevsky, 2017). Although it is difficult to make direct comparisons between results in the open field, which contains no bedding and is 1.5–10 × larger in area than the 4.5″ × 8.5″ home-cages we use in our study, it is clear that activity patterns in a short-duration novel environment greatly differ from activity patterns in the undisturbed home-cage.…”

Mice lacking galectin-3 (Lgals3) function have decreased home cage movement

“…Metabolic parameters were then adjusted for mouse adiposity and mouse lean body mass using ANCOVA [ 40 , 41 ]. Full description of our metabolic testing apparatus is provided in [ 42 ]. Mice were weighed using a Scout Pro SP401 (Ohaus, Parsippany NJ) before indirect calorimetry, home cage behavioral monitoring, and on a weekly basis between the two longitudinal assessments and following the last assessment.…”

“…Following data quality control, individual mouse feeding, drinking, and movement events were classified to determine active and inactive state properties (in a manner similar to human actigraphy), and to fit these behaviors to a Gaussian mixture model that would allow us to compare bout structures across genotypes. Theory and implementation of these processes has been published in [ 42 , 43 (both manuscript and data supplement), 44 ].…”

Toll-Like Receptor 2 Is a Regulator of Circadian Active and Inactive State Consolidation in C57BL/6 Mice

“…These metabolic parameters were adjusted for mouse adiposity per ANCOVA (Tschöp et al, 2012 ). Full details regarding our system components and operation are provided in Bonasera et al ( 2017 ).…”

“…We employ false discovery rate (FDR) statistics to minimize family-wise error rates; behaviors found significant in this manner are subjected to further analysis. Full details regarding our system hardware and software characteristics have been published (Goulding et al, 2008 ; Parkison et al, 2012 ; Bonasera et al, 2017 ).…”